Netskope, a provider of modern security solutions for the cloud and artificial intelligence (AI) era, has announced the launch of 'Netskope One Data Lineage'. This solution offers organisations enhanced visibility and analytics capabilities, allowing them to track and evaluate the provenance of data, irrespective of its location or movement.
The introduction of Netskope One Data Lineage is part of the ongoing expansion of the Netskope One platform, enabling organisations to advance their AI roadmaps with a verifiable audit trail for compliance, as well as support for data policy implementation and event investigations.
AI adoption requires governance of an organisation’s data, supported by a verifiable audit trail. Legacy data loss prevention tools often struggle to correlate data activity across sources and users, making it challenging to achieve comprehensive data visibility and protection.
Netskope One Data Lineage builds on Netskope’s data security controls. It enables organisations to track sensitive data movement throughout the enterprise, visualising its journey from origin to destination. The solution also provides insight into data propagation and evolution, even as it is reformatted across different files and formats.
Intended benefits of Netskope One Data Lineage include:
- Visibility and control: Organisations gain insight into data provenance, supporting retrospective investigations following data breaches or inappropriate internal access.
- Insider threat protection: Tracking inappropriate data movements and individual user behaviours allows potential insider risks to be identified and addressed.
- Policy and security posture: An extensive historical timeline of document origination enables IT teams to adjust data access policies to improve security.
Commenting on the launch, Krishna Narayanaswamy, Co-founder and CTO of Netskope, emphasised the importance of understanding how data moves across the digital environment and preventing unauthorised access, especially with increasing data protection regulations and the adoption of AI tools.
Jennifer Glenn from IDC Security and Trust Group noted that successful AI implementation relies on trust in the underlying data. As the volume of sensitive data grows, strict governance and verifiable audit trails ensure that only authorised entities access the appropriate information, providing a foundation for AI use.
